google-colaboratory

问题 Given the timing of Google Colab, I usually store my Google Drive activities in a DDMMYY folder (Day, month and year). Every day the content is stored like this. Images, code, drafts, etc. I mount Google Drive using the default form of Google Colab and not PyDrive from google.colab import drive drive.mount('/content/gdrive',force_remount=True) Is there any way to generate title + ID of all folder contents of the day (DDMMYY) in a list (csv, xml or json)? 回答1: This metadata is stored in

问题 I have been trying to get the TPUs working for a classification project. The dataset is quite big, ~150gb, so I cannot load it all in memory. Thus I have been using Dask. Dask doesn't integrate with tf.Dataset directly so I have to create a loader inspired by parallelising tf.data.Dataset.from_generator The dataset generates correctly when replacing the .fit with: iterator = ds.make_one_shot_iterator() next_element = iterator.get_next() with tf.Session() as sess: for i in range(1): val = sess

问题 I use GoogleColab to test data stuctures like chain-hashmap,probe-hashmap,AVL-tree,red-black-tree,splay-tree(written in Python),and I store very large dataset(key-value pairs) with these data stuctures to test some operation running time,its scale just like a small wikipedia,so run these python script will use very much memory(RAM),GoogleColab offers a approximately 12G RAM but not enough for me,these python scripts will use about 20-30G RAM,so when I run python program in GoogleColab,will

问题 I am trying to train my Deep Learning model on Google colab where they offer a free K80 GPU. I learned that it can be used for 12 hours at a time and then you have to reconnect to it. But my connection is lost after 10-15 minutes and I cannot reconnect (it stays stuck on Initializing) . What's the issue here ? 回答1: I have been able to running a vision training model and it disconnects and stops sometime overnight. It runs hours and may be 12 hours. I also trained the model using the CPU and

问题 When I use saver = tf.train.Saver() and save_path = saver.save(session, "checkpointsFolder/checkpoint.ckpt") I get a UnimplementedError (see above for traceback): File system scheme '[local]' not implemented error Here is the full error --------------------------------------------------------------------------- UnimplementedError Traceback (most recent call last) /usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args) 1333 try: -> 1334 return fn

问题 I am conducting a research which requires me to know the memory used during run time by the model when i run a deep learning model(CNN) in google colab. Is there any code i can use to know the same .Basically I want to know how much memory has been used in total model run .(after all epoch has been complete). I am coding in python Regards Avik 回答1: As explained in this post and my own observations, Tensorflow always tries to allocate the entire memory , no matter how small or big is your

问题 Is it possible to send query parameters via POST or GET to a Google Colab notebook? (And also have the response be either plaintext or structured json) How to retrieve the query in Colab? How do you sanitize or suppress the other output so that only plaintext or json is returned to the endpoint call? 回答1: You can make direct HTTP requests to the backend from FE Javascript. Here's an example notebook. Reproducing the key bits: A webserver can be started on the kernel to serve up arbitrary

问题 I am looking for a way to download an entire google drive folder from the publicly shared google drive folder link, without having to give my Google credentials. This SO question shows how to download the entire contents of a publicly shared Google Drive folder , but it requires Pydrive to access your Google credentials. Python: How do download entire folder from Google Drive And this code is able to download a single publicly shared google drive file without giving access to Google

问题 I have a google spreadsheet and it has 31 tabs(the 31 days). What I want to do is to use my code to reformat the data (which I have solved), but I can't figure out how to use a for loop to apply the code to all 31 tabs/days. Since each tab is one day of the month, I want the code to go to the first tab, apply the code, and then jump to the next tab and apply the same code. I want this process to go on until it finishes with all 31 tabs. Below is the code that I have tried, but it doesn't seem

问题 I am training 5 CNN's with MNIST on Google Colab. Whenever I go to check on it to see if the program is done, the notebook becomes unresponsive. My computers memory max's out and the cpu spikes and then the webpage crashes and shows the "Not enough memory to open this page" error. Has anyone else had an issue like this? Edit: Link to notebook: https://colab.research.google.com/drive/1EZ18Tf9RTwJB-Myy5YAK6py-SG_bNyDe 回答1: You can organize your code in sections and then collapse the sections